class_docstr: Multi-Scale STFT (MS-STFT) discriminator.
  
  Args:
      filters (int): Number of filters in convolutions.
      in_channels (int): Number of input channels.
      out_channels (int): Number of output channels.
      sep_channels (bool): Separate channels to distinct samples for stereo support.
      n_ffts (Sequence[int]): Size of FFT for each scale.
      hop_lengths (Sequence[int]): Length of hop between STFT windows for each scale.
      win_lengths (Sequence[int]): Window size for each scale.
      **kwargs: Additional args for STFTDiscriminator.
class_docstr_tok: ["Multi-Scale","STFT","(","MS-STFT",")","discriminator",".","Args",":","filters","(","int",")",":","Number","of","filters","in","convolutions",".","in_channels","(","int",")",":","Number","of","input","channels",".","out_channels","(","int",")",":","Number","of","output","channels",".","sep_channels","(","bool",")",":","Separate","channels","to","distinct","samples","for","stereo","support",".","n_ffts","(","Sequence","[","int","]",")",":","Size","of","FFT","for","each","scale",".","hop_lengths","(","Sequence","[","int","]",")",":","Length","of","hop","between","STFT","windows","for","each","scale",".","win_lengths","(","Sequence","[","int","]",")",":","Window","size","for","each","scale",".","*","*","kwargs",":","Additional","args","for","STFTDiscriminator","."]
code: def _separate_channels(self, x: torch.Tensor) -> torch.Tensor:
      B, C, T = x.shape
      return x.view(-1, 1, T)
  
file_path: audiocraft/audiocraft/adversarial/discriminators/msstftd.py
imports: import typing
  import torchaudio
  import torch
  from torch import nn
  from einops import rearrange
  from ...modules import NormConv2d
  from .base import MultiDiscriminator, MultiDiscriminatorOutputType
label_desc: Use image node_id 3 for calling the MultiScaleSTFTDiscriminator obj's underlying member method code with example usage: obj._separate_channels(x) and returns: x